def perturb(rpath, wpath, kl_path, Z_path, dth_path, nkl):
# inputs
# Z_path : where to write out the sample normal
# dth_path : where to write out the random rotation
# nkl : where to truncate the K-L expansion
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# translate blade random amount (rotate about x axis)
random.seed()
dth = random.randn(1)*pi/180*0.1/3.0
for i in range(cdim):
for j in range(sdim):
r = sqrt(y[i,j]**2 + z[i,j]**2)
th = math.atan2(z[i,j],y[i,j])
y[i,j] = r*cos(th+dth)
z[i,j] = r*sin(th+dth)
# write out dth
f = open(dth_path,'w')
f.write('%e\n' % dth)
f.close()
# generate and write out the Z for this mesh
random.seed()
Z = random.randn(nkl) # normal distribution vector
f = open(Z_path,'w')
for i in range(nkl):
f.write('%e\n' % Z[i])
f.close()
# read in PCA modes and singular values
lines = file(kl_path+'S.dat').readlines()
S = array([line.strip().split()[0] for line in lines], float).T
n_modes = len(S)
fp = zeros((cdim,sdim))
for i in range(nkl):
cdim,sdim,V = read_blade.read_mode(kl_path+'V'+str(i+1)+'.dat')
fp += Z[i]*sqrt(S[i])*V
np = read_blade.calcNormals(x,y,z)
xp = x + np[:,:,0]*fp
yp = y + np[:,:,1]*fp
zp = z + np[:,:,2]*fp
# write out the blade surface
f = open(wpath,'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i,j],yp[i,j],zp[i,j]))
f.write('\n')
f.close()
# write out to tecplot format
write_tecplot.write_blade_surf(xp,yp,zp,fp,'blade.dat')
def perturb_rot(rpath, wpath, dth):
# dht - amount to rotate blade
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# split the blade
xu,yu,zu,xl,yl,zl = read_blade.split_blade(cdim,sdim,x,y,z)
xle = xu[0,0]; yle = yu[0,0]
xte = xu[-1,0]; yte = yu[-1,0]
th = arctan2(y-yle,x-xle)
r = sqrt((x-xle)**2 + (y-yle)**2)
xp = xle + r*cos(th+dth)
yp = yle + r*sin(th+dth)
zp = copy(z)
pylab.plot(x[:,0],y[:,0])
pylab.plot(xp[:,0],yp[:,0])
pylab.axis('Equal')
pylab.show()
# write out the blade surface
f = open(wpath,'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i,j],yp[i,j],zp[i,j]))
f.write('\n')
f.close()
# write out to tecplot format
write_tecplot.write_blade_surf(xp,yp,zp,'tec_blade.dat')
def perturb(rpath, wpath, pca_path, scale, mode):
# inputs
# Z_path : where to write out the sample normal
# npca : where to truncate the PCA expansion
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# perturb using only one of the transformed modes
lines = file(pca_path+'S.dat').readlines()
S = array([line.strip().split()[0] for line in lines], float).T
fp = zeros((cdim,sdim))
cdim,sdim,V = read_blade.read_mode(pca_path+'V'+str(mode)+'.dat')
fp += scale*S[mode-1]*V
np = read_blade.calcNormals(x,y,z)
xp = x + np[:,:,0]*fp
yp = y + np[:,:,1]*fp
zp = z + np[:,:,2]*fp
# write out the blade surface
f = open(wpath,'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i,j],yp[i,j],zp[i,j]))
f.write('\n')
f.close()
# test to see how they look
'''
i = 3
cdim,sdim,V = read_blade.read_mode(pca_path+'V'+str(i+1)+'.dat')
s, t = read_blade.xyz2st(x,y,z)
print s[0],s[1]
pylab.contourf(s,t,V.T,50)
pylab.colorbar()
pylab.show()
'''
'''
fig = pylab.figure()
ax = Axes3D(fig)
surf = ax.plot_surface(sg, tg, fp, rstride=1, cstride=1, cmap = cm.jet)
'''
'''
fig = pylab.figure()
ax = Axes3D(fig)
surf = ax.plot_surface(tg, sg, nf[1:-1,1:-1,2], rstride=1, cstride=1, cmap = cm.jet)
# fig.colorbar(surf)
'''
'''
def perturb_chev(rpath, wpath, M):
# M - amplitudes of the Chevyshev modes
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# split the blade
xu,yu,zu,xl,yl,zl = read_blade.split_blade(cdim,sdim,x,y,z)
# compute the s coordinates
tck, su = splprep([xu[:,0],yu[:,0]],s=0)
tck, sl = splprep([xl[:,0],yl[:,0]],s=0)
# form the modes
nmodes = len(M)
cheb = zeros((nmodes,x.shape[0],x.shape[1]))
for i in arange(nmodes):
n = i + 1
if mod(n,2) == 0:
gu = (1-2*su-cos((n+1)*arccos(1-2*su)))/(n+1.)
gl = -(1-2*sl-cos((n+1)*arccos(1-2*sl)))/(n+1.)
cheb[i,:,:] = tile(hstack((gu,gl[::-1][1:])),(sdim,1)).T
else:
gu = (1-cos((n+1)*arccos(1-2*su)))/(n+1.)
gl = -(1-cos((n+1)*arccos(1-2*sl)))/(n+1.)
cheb[i,:,:] = tile(hstack((gu,gl[::-1][1:])),(sdim,1)).T
np = read_blade.calcNormals(x,y,z)
for i in arange(nmodes):
xp = x + np[:,:,0]*cheb[i,:,:]*M[i]
yp = y + np[:,:,1]*cheb[i,:,:]*M[i]
zp = z + np[:,:,2]*cheb[i,:,:]*M[i]
pylab.plot(x[:,0],y[:,0])
pylab.plot(xp[:,0],yp[:,0])
pylab.axis('Equal')
pylab.show()
# write out the blade surface
f = open(wpath,'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i,j],yp[i,j],zp[i,j]))
f.write('\n')
f.close()
# write out to tecplot format
write_tecplot.write_blade_surf(xp,yp,zp,'tec_blade.dat')
def perturb_chev(rpath, wpath, M):
# M - amplitudes of the Chevyshev modes
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# split the blade
xu, yu, zu, xl, yl, zl = read_blade.split_blade(cdim, sdim, x, y, z)
# compute the s coordinates
tck, su = splprep([xu[:, 0], yu[:, 0]], s=0)
tck, sl = splprep([xl[:, 0], yl[:, 0]], s=0)
# form the modes
nmodes = len(M)
cheb = zeros((nmodes, x.shape[0], x.shape[1]))
for i in arange(nmodes):
n = i + 1
if mod(n, 2) == 0:
gu = (1 - 2 * su - cos((n + 1) * arccos(1 - 2 * su))) / (n + 1.)
gl = -(1 - 2 * sl - cos((n + 1) * arccos(1 - 2 * sl))) / (n + 1.)
cheb[i, :, :] = tile(hstack((gu, gl[::-1][1:])), (sdim, 1)).T
else:
gu = (1 - cos((n + 1) * arccos(1 - 2 * su))) / (n + 1.)
gl = -(1 - cos((n + 1) * arccos(1 - 2 * sl))) / (n + 1.)
cheb[i, :, :] = tile(hstack((gu, gl[::-1][1:])), (sdim, 1)).T
np = read_blade.calcNormals(x, y, z)
for i in arange(nmodes):
xp = x + np[:, :, 0] * cheb[i, :, :] * M[i]
yp = y + np[:, :, 1] * cheb[i, :, :] * M[i]
zp = z + np[:, :, 2] * cheb[i, :, :] * M[i]
pylab.plot(x[:, 0], y[:, 0])
pylab.plot(xp[:, 0], yp[:, 0])
pylab.axis('Equal')
pylab.show()
# write out the blade surface
f = open(wpath, 'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i, j], yp[i, j], zp[i, j]))
f.write('\n')
f.close()
# write out to tecplot format
write_tecplot.write_blade_surf(xp, yp, zp, 'tec_blade.dat')
def perturb_rot(rpath, wpath, dth):
# dht - amount to rotate blade
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# split the blade
xu, yu, zu, xl, yl, zl = read_blade.split_blade(cdim, sdim, x, y, z)
xle = xu[0, 0]
yle = yu[0, 0]
xte = xu[-1, 0]
yte = yu[-1, 0]
th = arctan2(y - yle, x - xle)
r = sqrt((x - xle)**2 + (y - yle)**2)
xp = xle + r * cos(th + dth)
yp = yle + r * sin(th + dth)
zp = copy(z)
pylab.plot(x[:, 0], y[:, 0])
pylab.plot(xp[:, 0], yp[:, 0])
pylab.axis('Equal')
pylab.show()
# write out the blade surface
f = open(wpath, 'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i, j], yp[i, j], zp[i, j]))
f.write('\n')
f.close()
# write out to tecplot format
write_tecplot.write_blade_surf(xp, yp, zp, 'tec_blade.dat')
def perturb(rpath, wpath):
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# scale coordinates to be in cm
scale = 1.0
x *= scale
y *= scale
z *= scale
xu, yu, zu, xl, yl, zl = read_blade.split_blade(cdim, sdim, x, y, z)
xmc = 0.5*(xu+xl)
ymc = 0.5*(yu+yl)
zmc = 0.5*(zu+zl)
dx = xu - xmc
dy = yu - ymc
dz = zu - zmc
# camber random process
sc,tc = read_blade.xyz2st(xmc,ymc,zmc)
ns = xmc.shape[0]
nt = xmc.shape[1]
# mode cutoff
Ks = ns
Kt = nt
fc = simulate.randProcess(sc, tc, ns, nt, Ks, Kt)
tg, sg = meshgrid(tc,sc)
nc = read_blade.calcNormals(xmc,ymc,zmc)
xmc = xmc + nc[:,:,0]*fc
ymc = ymc + nc[:,:,1]*fc
zmc = zmc + nc[:,:,2]*fc
xu = xmc + dx
yu = ymc + dy
zu = zmc + dz
xl = xmc - dx
yl = ymc - dy
zl = zmc - dz
xp = vstack((xu[:-1,:],xl[::-1,:]))
yp = vstack((yu[:-1,:],yl[::-1,:]))
zp = vstack((zu[:-1,:],zl[::-1,:]))
# normal random process
sp,tp = read_blade.xyz2st(xp,yp,zp)
ns = xp.shape[0]
nt = xp.shape[1]
Ks = ns
Kt = nt
fp = simulate.randProcessPeriodic(sp, tp, ns, nt, Ks, Kt)
fp[0,:] = fp[-1,:]
# fp = zeros(fp.shape)
'''
# interpolate back to original mesh
ss = linspace(0,sp[-1]-sp[0],ns)
tt = linspace(0,tp[-1]-tp[0],nt)
ff = simulate.randProcessPeriodic(ss, tt, ns, nt, Ks, Kt)
fp = simulate.interp(ss, tt, ff, sp, tp)
tg, sg = meshgrid(tt,ss)
pylab.contourf(sg,tg,ff,30)
pylab.contourf(sg+sg[-1],tg,ff,30)
pylab.colorbar()
pylab.axes().set_aspect('equal', 'datalim')
pylab.figure()
'''
tg, sg = meshgrid(tp,sp)
pylab.contourf(sg,tg,fp,30)
# pylab.contourf(sg+sg[-1],tg,fp,30)
pylab.colorbar()
pylab.xlim(0.0,sp[-1])
pylab.axes().set_aspect('equal', 'datalim')
pylab.xlabel('x')
pylab.ylabel('y')
pylab.show()
np = read_blade.calcNormals(xp,yp,zp)
xp = xp + np[:,:,0]*fp
yp = yp + np[:,:,1]*fp
zp = zp + np[:,:,2]*fp
# scale coordinates back to original units
x /= scale
y /= scale
z /= scale
xp /= scale
yp /= scale
zp /= scale
# write out the blade surface
f = open(wpath,'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i,j],yp[i,j],zp[i,j]))
f.write('\n')
f.close()
# write out the normal perturbation
g = open('normal_field.dat','w')
for i in arange(cdim):
for j in arange(sdim):
g.write('%20.8E' * 4 % (x[i,j],y[i,j],z[i,j],fp[i,j]))
g.write('\n')
g.close()
'''
fig = pylab.figure()
ax = Axes3D(fig)
surf = ax.plot_surface(sg, tg, fp, rstride=1, cstride=1, cmap = cm.jet)
'''
'''
fig = pylab.figure()
ax = Axes3D(fig)
surf = ax.plot_surface(tg, sg, nf[1:-1,1:-1,2], rstride=1, cstride=1, cmap = cm.jet)
# fig.colorbar(surf)
'''
'''
J = linalg.lstsq(A,Y)[0][1:]
# form the stacked Jacobian
if isim == 0:
stackJ = J.T
else:
stackJ = vstack([stackJ, J.T])
# mean of the Jacobians
meanJ = mean(stackJ,axis=0)
# compute SVD of stacked Jacobian
V,S,UT = linalg.svd(stackJ)
# read in the surface mesh
rpath = '/mnt/pwfiles/ericdow/random_blade/input/rotor37_coarse/blade_surf.dat'
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# read in the PCA modes
pca_path = '/mnt/pwfiles/ericdow/random_blade/input/rotor37_coarse/pca_modes_gp/'
V_pca = zeros((NZ,cdim,sdim))
for i in range(NZ):
cdim,sdim,V_pca[i,:,:] = read_blade.read_mode(pca_path+'V'+str(i+1)+'.dat')
V_pca_tmp = zeros((NZ,cdim*sdim))
for i in range(NZ):
V_pca_tmp[i,:] = reshape(V_pca[i,:,:],(cdim*sdim))
# transform the modes
V_trans_tmp = dot(dot(UT.T,eye(NZ)*S_pca),V_pca_tmp)
V_trans = zeros((NZ,cdim,sdim))
import pylab, os, math, string
from numpy import *
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import read_blade
inp = '/mnt/pwfiles/ericdow/random_blade/input/rotor37_coarse/'
rundir = '/mnt/pwfiles/ericdow/random_blade/runs/'
# read in original blade surface
cdim, sdim, xn, yn, zn = read_blade.read_coords(inp+'blade_surf.dat')
# read in blade surfaces of completed runs
iran = zeros((len(os.listdir(rundir))))
i = 0
for rd in os.listdir(rundir):
if os.path.exists(rundir+str(rd)+'/utcfd_out.monitoring.dat'):
lines = file(rundir+str(rd)+'/utcfd_out.monitoring.dat').readlines()
if lines[-1][1:4] == 'Job':
iran[i] = 1
lines = file(rundir+str(rd)+'/Z.dat').readlines()
npca = len(lines)
i += 1
nruns = int(sum(iran))
# perturbed coordinates
xp = zeros((nruns,cdim,sdim))
yp = zeros((nruns,cdim,sdim))
zp = zeros((nruns,cdim,sdim))
def perturb(rpath, wpath, pca_path, Z_path, npca):
# inputs
# Z_path : where to write out the sample normal
# npca : where to truncate the PCA expansion
cdim, sdim, x, y, z = read_blade.read_coords(rpath)
# generate and write out the Z for this mesh
random.seed()
Z = random.randn(npca) # normal distribution vector
f = open(Z_path,'w')
for i in range(npca):
f.write('%e\n' % Z[i])
f.close()
################################
# SCALE PCA MODES BY CHORD RATIO
################################
# r5_chord = 0.859 # inches at hub
# r37_chord = 2.17 # inches at hub
# scale = r37_chord/r5_chord
scale = 1.0
# read in PCA modes and singular values
lines = file(pca_path+'S.dat').readlines()
S = array([line.strip().split()[0] for line in lines], float).T
n_modes = len(S)
# add the mean
cdim,sdim,fp = read_blade.read_mode(pca_path+'mean.dat')
# add the PCA modes
for i in range(npca):
cdim,sdim,V = read_blade.read_mode(pca_path+'V'+str(i+1)+'.dat')
fp += scale*Z[i]*S[i]*V
np = read_blade.calcNormals(x,y,z)
xp = x + np[:,:,0]*fp
yp = y + np[:,:,1]*fp
zp = z + np[:,:,2]*fp
# write out the blade surface
f = open(wpath,'w')
f.write('CDIM: %d\n' % cdim)
f.write('SDIM: %d\n' % sdim)
for i in arange(cdim):
for j in arange(sdim):
f.write('%20.8E' * 3 % (xp[i,j],yp[i,j],zp[i,j]))
f.write('\n')
f.close()
# write out to tecplot format
# write_tecplot.write_blade_surf(xp,yp,zp,fp,'blade.dat')
# test to see how they look
'''
i = 3
cdim,sdim,V = read_blade.read_mode(pca_path+'V'+str(i+1)+'.dat')
s, t = read_blade.xyz2st(x,y,z)
print s[0],s[1]
pylab.contourf(s,t,V.T,50)
pylab.colorbar()
pylab.show()
'''
'''
fig = pylab.figure()
ax = Axes3D(fig)
surf = ax.plot_surface(sg, tg, fp, rstride=1, cstride=1, cmap = cm.jet)
'''
'''
fig = pylab.figure()
ax = Axes3D(fig)
surf = ax.plot_surface(tg, sg, nf[1:-1,1:-1,2], rstride=1, cstride=1, cmap = cm.jet)
# fig.colorbar(surf)
'''
'''